llmsmap.ru

Независимый технический аудит

docs.datafold.com

docs.datafold.com

Итоговая оценка ИИ-оптимизации

Сводный результат по всем сигналам аудита.

73из 100Средне
Проверка ИИ-оптимизации: 05.10.2026Публичные технические данные

Итоговая оценка ИИ-оптимизации

Насколько docs.datafold.com оптимизирован для работы с ИИ

73/100

Datafold (docs.datafold.com) получил 73/100 по результатам автоматического технического аудита готовности к работе с ИИ. Файл llms.txt доступен, llms-full.txt доступен, ai.txt не найден. Анализ robots.txt показал: явно разрешено ИИ-ботов — 0, заблокировано — 0, объявлено sitemap — 1. Полнота разметки главной страницы — 0%; типы Schema.org не обнаружены, OpenGraph-тегов — 0. Результаты соответствуют публичным ответам сайта на момент проверки 2026-10-05T12:16:05.604Z.

Контекст итоговой оценки

Файл llms.txt доступен и содержит 8 466 токенов. Расширенный llms-full.txt также найден; его объём — 122 795 токенов, поэтому агент может получить более полный контекст без обхода всего сайта. Отдельный ai.txt не обнаружен; это не обязательная часть предлагаемого формата llms.txt, но такой файл может явно описать политику обучения, цитирования и автоматического доступа.

robots.txt доступен. Из 11 отслеживаемых ИИ-ботов 11 не заблокированы. Объявлено карт сайта: 1. На главной не обнаружена Schema.org-разметка. OpenGraph-тегов найдено 0, расчётная полнота публичной разметки — 0%. Без сущностей и связей ИИ сложнее однозначно определить организацию, продукт и канонические страницы.

Мобильный профиль Lighthouse дополняет аудит: производительность 39/100, доступность 92/100, технические практики 92/100, SEO 92/100 и экспериментальная готовность браузерных агентов 100/100. Эти данные входят в итоговую оценку ИИ-оптимизации с ограниченным весом: они дополняют, но не заменяют проверку llms.txt, robots.txt и машинной разметки.

Подтверждённые сильные стороны

  • llms.txt доступен
  • Есть расширенный llms-full.txt
  • Объявлено sitemap: 1
  • Сильные agentic-сигналы Google

Приоритетные улучшения

  1. 1Добавить JSON-LD для организации, сайта и основных сущностей.
  2. 2Дополнить OpenGraph и канонические метаданные главной страницы.
  3. 3Сократить задержки мобильного рендера и занятость основного потока.
Токены llms.txt8 466
Токены llms-full.txt122 795
ai.txt
sitemap.xml

Технический профиль Google Lighthouse

Замер мобильной версии. Экспериментальная категория Google Agentic Browsing показана отдельно и не заменяет итоговую оценку ИИ-оптимизации от llmsmap.

Мобильная версия · Lighthouse
39

Производительность

92

Доступность

92

Технические практики

92

Техническое SEO

100

Работа браузерных агентов

Что означают результаты

Производительность мобильной версии — 39/100; самый крупный видимый блок появился за 13.9 s, а суммарная блокировка основного потока составила 960 ms. Показатель смещения макета — 0. Основной поток выполняет JavaScript, рассчитывает расположение элементов и рисует страницу: пока он занят, интерфейс хуже реагирует и на действия человека, и на команды браузерного агента.

Доступность получила 92/100, технические практики — 92/100, SEO — 92/100. Экспериментальная категория Agentic Browsing получила 100/100. Она отражает сигналы, которые Google сейчас проверяет для программных агентов, и не заменяет итоговую оценку ИИ-оптимизации от llmsmap.

1

Освободить основной поток и ускорить первый экран

Разделите длинные JavaScript-задачи, отложите необязательные скрипты и критические стили, уменьшите цепочки блокирующих запросов. Это ускорит появление основного контента и позволит интерфейсу раньше принимать действия.

2

Сократить код, который загружается без пользы

Удалите неиспользуемые CSS и JavaScript, загружайте тяжёлые виджеты по необходимости и ограничьте сторонние скрипты. Меньший объём кода снижает нагрузку на устройство и количество фоновой работы.

3

Оптимизировать изображения и порядок их загрузки

Отдавайте изображения в подходящем размере и современном формате, заранее приоритизируйте главный визуальный блок, а контент ниже первого экрана загружайте лениво.

4

Сократить сетевые задержки

Уменьшите время ответа сервера, лишние редиректы и повторные загрузки; настройте сжатие, кеширование и ранние соединения только с действительно важными источниками.

FCP4.4 s

Первый контент

LCP13.9 s

Главный блок

CLS0

Стабильность

TBT960 ms

Блокировка

SI6.6 s

Скорость экрана

Расшифровка показателей
FCP · Первый контент
Когда на экране появился первый текст или изображение.
LCP · Главный блок
Когда отрисовался самый крупный видимый элемент первого экрана.
CLS · Стабильность
Насколько сильно элементы неожиданно смещались при загрузке; меньше — лучше.
TBT · Блокировка
Сколько времени основной поток не мог быстро ответить на действие.
SI · Скорость экрана
Насколько быстро видимая область страницы заполнилась контентом.
05.10.2026Lighthouse 13.5.0Мобильный профиль

Проверки ИИ-оптимизации

Машиночитаемые файлы, правила краулинга, обнаружение страниц и разметка главной.

llms.txt

Файл найден и доступен

https://docs.datafold.com/llms.txt
llms-full.txt

Полная версия доступна

https://docs.datafold.com/llms-full.txt
ai.txt

Файл ai.txt не найден

robots.txt

Файл найден

https://docs.datafold.com/robots.txt
Sitemap в robots.txt1 шт.

Найдено карт сайта: 1

Schema.org (JSON-LD)

Разметка Schema.org не найдена на главной

OpenGraph

OpenGraph теги не найдены на главной

Доступ ИИ-ботов

На основе анализа robots.txt

GPTBotНе упомянут
OAI-SearchBotНе упомянут
ChatGPT-UserНе упомянут
Google-ExtendedНе упомянут
ClaudeBotНе упомянут
Claude-SearchBotНе упомянут
Claude-UserНе упомянут
BytespiderНе упомянут
CCBotНе упомянут
PerplexityBotНе упомянут
Perplexity-UserНе упомянут

Карты сайта

Объявленные маршруты для поисковых роботов и ИИ-агентов.

# Datafold

- [Datafold](https://docs.datafold.com/welcome.md): Datafold is the data engineering automation platform that combines specialized AI agents with a context layer and data quality tools — so data teams and their coding agents ship higher-quality data faster, migrate with confidence, and optimize platform costs.
- [MCP](https://docs.datafold.com/datafold-mcp.md): Connect your AI agent to Datafold and interact with your data through natural language
- [Migration Automation](https://docs.datafold.com/data-migration-automation/datafold-migration-automation.md): Modernize your data platform in weeks, not years. Datafold's Data Migration Agent delivers guaranteed-outcome migrations with fixed price, timeline, and data parity — over 6x faster and cheaper than traditional approaches.
- [Datafold Migration Agent](https://docs.datafold.com/data-migration-automation/datafold-migration-agent.md): The Data Migration Agent delivers guaranteed-outcome migrations with fixed price, timeline, and data parity — over 6x faster than traditional approaches.
- [What's a Data Diff?](https://docs.datafold.com/data-diff/what-is-data-diff.md): A data diff is the value-level comparison between two tables, used to identify critical changes to your data and guarantee data quality.
- [How Datafold Diffs Data](https://docs.datafold.com/data-diff/how-datafold-diffs-data.md): Data diffs allow you to perform value-level comparisons between any two datasets within the same database, across different databases, or even between files.
- [Creating a New Data Diff](https://docs.datafold.com/data-diff/in-database-diffing/creating-a-new-data-diff.md): Setting up a new data diff in Datafold is straightforward.
- [Results](https://docs.datafold.com/data-diff/in-database-diffing/results.md): Once your data diff is complete, Datafold provides a concise, high-level summary of the detected changes in the Overview tab
- [Best Practices](https://docs.datafold.com/data-diff/in-database-diffing/best-practices.md): We share best practices that will help you get the most accurate and efficient results from your data diffs.
- [Creating a New Data Diff](https://docs.datafold.com/data-diff/cross-database-diffing/creating-a-new-data-diff.md): Datafold's Data Diff can compare data across databases (e.g., PostgreSQL <> Snowflake, or between two SQL Server instances) to validate migrations, meet regulatory and compliance requirements, or ensure data is flowing successfully from source to target.
- [Results](https://docs.datafold.com/data-diff/cross-database-diffing/results.md): Once your data diff is complete, Datafold provides a concise, high-level summary of the detected changes in the Overview tab.
- [Best Practices](https://docs.datafold.com/data-diff/cross-database-diffing/best-practices.md): When dealing with large datasets, it's crucial to approach diffing with specific optimization strategies in mind. We share best practices that will help you get the most accurate and efficient results from your data diffs.
- [How Datafold in CI Works](https://docs.datafold.com/deployment-testing/how-it-works.md): Learn how Datafold integrates with your Continuous Integration (CI) process with Data Diffs and AI Code Reviews, catching issues before they make it into production.
- [AI Code Reviews](https://docs.datafold.com/deployment-testing/ai-code-reviews.md): Get automated, AI-powered code reviews on every pull request to catch SQL and data pipeline issues before they reach production.
- [Getting Started with CI/CD Testing](https://docs.datafold.com/deployment-testing/getting-started.md): Learn how to set up CI/CD testing with Datafold by integrating your data connections, code repositories, and CI pipeline for automated testing.
- [No-Code](https://docs.datafold.com/deployment-testing/getting-started/universal/no-code.md): Set up Datafold's No-Code CI integration to create and manage Data Diffs without writing code.
- [API](https://docs.datafold.com/deployment-testing/getting-started/universal/api.md): Learn how to set up and configure Datafold's API for CI/CD testing.
- [Configuration](https://docs.datafold.com/deployment-testing/configuration.md): Explore configuration options for CI/CD testing in Datafold.
- [Primary Key Inference](https://docs.datafold.com/deployment-testing/configuration/primary-key.md): Datafold requires a primary key to perform data diffs. Using dbt metadata, Datafold identifies the column to use as the primary key for accurate data diffs.
- [Column Remapping](https://docs.datafold.com/deployment-testing/configuration/column-remapping.md): Specify column renaming in your git commit message so Datafold can map renamed columns to their original counterparts in production for accurate comparison.
- [Running Data Diff for Specific PRs/MRs](https://docs.datafold.com/deployment-testing/configuration/datafold-ci/on-demand.md): By default, Datafold CI runs on every new pull/merge request and commits to existing ones.
- [Running Data Diff on Specific Branches](https://docs.datafold.com/deployment-testing/configuration/datafold-ci/specifc.md): By default, Datafold CI runs on every new pull/merge request and commits to existing ones.
- [SQL Filters](https://docs.datafold.com/deployment-testing/configuration/model-specific-ci/sql-filters.md): Use dbt YAML configuration to set model-specific filters for Datafold CI.
- [Time Travel](https://docs.datafold.com/deployment-testing/configuration/model-specific-ci/time-travel.md): Use `prod_time_travel` and `pr_time_travel` to diff tables from specific points in time.
- [Including/Excluding Columns](https://docs.datafold.com/deployment-testing/configuration/model-specific-ci/including-excluding-columns.md): Specify columns to include or exclude from the data diff using `include_columns` and `exclude_columns`.
- [Excluding Models](https://docs.datafold.com/deployment-testing/configuration/model-specific-ci/excluding-models.md): Use `never_diff` to exclude a model or subdirectory of models from data diffs.
- [Diff Timeline](https://docs.datafold.com/deployment-testing/configuration/model-specific-ci/diff-timeline.md): Specify a `time_column` to visualize match rates between tables for each column over time.
- [Slim Diff](https://docs.datafold.com/deployment-testing/best-practices/slim-diff.md): Choose which downstream tables to diff to optimize time, cost, and performance.
- [Handling Data Drift](https://docs.datafold.com/deployment-testing/best-practices/handling-data-drift.md): Ensuring Datafold in CI executes apples-to-apples comparison between staging and production environments.
- [Monitor Types](https://docs.datafold.com/data-monitoring/monitor-types.md): Monitoring your data for unexpected changes is one of the cornerstones of data observability.
- [Data Diff Monitors](https://docs.datafold.com/data-monitoring/monitors/data-diff-monitors.md): Data Diff monitors compare datasets across or within databases, identifying row and column discrepancies with customizable scheduling and notifications.
- [Metric Monitors](https://docs.datafold.com/data-monitoring/monitors/metric-monitors.md): Metric monitors detect anomalies in your data using ML-based algorithms or manual thresholds, supporting standard and custom metrics for tables or columns.
- [Data Test Monitors](https://docs.datafold.com/data-monitoring/monitors/data-test-monitors.md): Data Tests validate your data against off-the-shelf checks or custom business rules.
- [Schema Change Monitors](https://docs.datafold.com/data-monitoring/monitors/schema-change-monitors.md): Schema Change monitors notify you when a table’s schema changes, such as when columns are added, removed, or data types are modified.
- [Monitors as Code](https://docs.datafold.com/data-monitoring/monitors-as-code.md): Manage Datafold monitors via version-controlled YAML for greater scalability, governance, and flexibility in code-based workflows.
- [How It Works](https://docs.datafold.com/data-explorer/how-it-works.md): Datafold's Data Knowledge Graph maps your entire data ecosystem — lineage, business logic, usage, and ontology — providing essential context to your AI agents via MCP and helping you understand the impact of changes across systems.
- [Lineage](https://docs.datafold.com/data-explorer/lineage.md): Datafold offers a column-level and tabular lineage view.
- [Profile](https://docs.datafold.com/data-explorer/profile.md): View a data profile that summarizes key table and column-level statistics, and any upstream dependencies.
- [dbt Metadata Sync](https://docs.datafold.com/data-explorer/best-practices/dbt-metadata-sync.md): Datafold can automatically ingest dbt metadata from your production environment and display it in Data Explorer.
- [Set Up Your Data Connection](https://docs.datafold.com/integrations/databases.md): Set up your Data Connection with Datafold.
- [Snowflake](https://docs.datafold.com/integrations/databases/snowflake.md): Connect Datafold to Snowflake for data diffing, CI/CD testing, lineage, and migration validation. Includes setup instructions and required permissions.
- [Snowflake key-pair authentication](https://docs.datafold.com/integrations/databases/snowflake-key-pair-authentication.md): Move an existing Datafold Snowflake connection from password to key-pair authentication and make the Datafold user a Snowflake SERVICE user before Snowflake blocks password sign-ins.
- [BigQuery](https://docs.datafold.com/integrations/databases/bigquery.md)
- [Athena](https://docs.datafold.com/integrations/databases/athena.md)
- [Redshift](https://docs.datafold.com/integrations/databases/redshift.md)
- [Databricks](https://docs.datafold.com/integrations/databases/databricks.md): Connect Datafold to Databricks for data diffing, CI/CD testing, lineage, and migration validation. Includes setup instructions and required permissions.
- [PostgreSQL](https://docs.datafold.com/integrations/databases/postgresql.md)
- [Microsoft SQL Server](https://docs.datafold.com/integrations/databases/sql-server.md): Connect Datafold to Microsoft SQL Server for data diffing, reconciliation, and migration validation. Includes setup instructions and required permissions.
- [Azure Synapse Analytics](https://docs.datafold.com/integrations/databases/synapse.md): Connect Datafold to Azure Synapse Analytics for data diffing, reconciliation, and migration validation. Includes setup instructions and required permissions.
- [Oracle](https://docs.datafold.com/integrations/databases/oracle.md): Connect Datafold to Oracle Database for data diffing, reconciliation, and migration validation. Includes setup instructions and required permissions.
- [MySQL](https://docs.datafold.com/integrations/databases/mysql.md)
- [Dremio](https://docs.datafold.com/integrations/databases/dremio.md)
- [SAP HANA](https://docs.datafold.com/integrations/databases/sap-hana.md)
- [Starburst](https://docs.datafold.com/integrations/databases/starburst.md)
- [Teradata](https://docs.datafold.com/integrations/databases/teradata.md)
- [Netezza](https://docs.datafold.com/integrations/databases/netezza.md)
- [OAuth Support](https://docs.datafold.com/integrations/oauth.md): Set up OAuth App Connections in your supported data warehouses to securely execute data diffs on behalf of your users.
- [Slack Bot](https://docs.datafold.com/integrations/agents/slack-bot.md): Datafold Assistant — a conversational Slack bot that answers questions about your data using Datafold's MCP tools, scoped via a service account.
- [Bring Your Own LLM Provider](https://docs.datafold.com/integrations/llm-providers.md): Run the Datafold Migration Agent on your own LLM inference provider and credentials.
- [OpenAI-compatible](https://docs.datafold.com/integrations/llm-providers/openai-compatible.md)
- [OpenAI](https://docs.datafold.com/integrations/llm-providers/openai.md)
- [Anthropic](https://docs.datafold.com/integrations/llm-providers/anthropic.md)
- [Google Gemini](https://docs.datafold.com/integrations/llm-providers/google-gemini.md)
- [Azure AI Foundry](https://docs.datafold.com/integrations/llm-providers/azure-ai-foundry.md)
- [AWS Bedrock](https://docs.datafold.com/integrations/llm-providers/aws-bedrock.md)
- [Google Vertex AI](https://docs.datafold.com/integrations/llm-providers/google-vertex-ai.md)
- [Databricks](https://docs.datafold.com/integrations/llm-providers/databricks.md)
- [Snowflake Cortex](https://docs.datafold.com/integrations/llm-providers/snowflake-cortex.md)
- [Integrate with Orchestrators](https://docs.datafold.com/integrations/orchestrators.md): Integrate Datafold with dbt Core, dbt Cloud, Airflow, or custom orchestrators to streamline your data workflows with automated monitoring, testing, and seamless CI integration.
- [dbt Core](https://docs.datafold.com/integrations/orchestrators/dbt-core.md): Set up Datafold’s integration with dbt Core to automate Data Diffs in your CI pipeline.
- [dbt Cloud](https://docs.datafold.com/integrations/orchestrators/dbt-cloud.md): Integrate Datafold with dbt Cloud to automate Data Diffs in your CI pipeline, leveraging dbt jobs to detect changes and ensure data quality before merging.
- [Custom Integrations](https://docs.datafold.com/integrations/orchestrators/custom-integrations.md): Integrate Datafold with your custom orchestration using the Datafold SDK and REST API.
- [Looker](https://docs.datafold.com/integrations/bi-data-apps/looker.md): Integrate Datafold with Looker to track BI lineage and understand the downstream impact of data changes on your Looker dashboards and Explores.
- [Tableau](https://docs.datafold.com/integrations/bi-data-apps/tableau.md): Visualize downstream Tableau dependencies and understand how warehouse changes impact your BI layer.
- [Power BI](https://docs.datafold.com/integrations/bi-data-apps/power-bi.md): Include Power BI entities in Data Explorer and column-level lineage.
- [Mode](https://docs.datafold.com/integrations/bi-data-apps/mode.md)
- [Hightouch](https://docs.datafold.com/integrations/bi-data-apps/hightouch.md): Navigate to Settings > Integrations > Data Apps and add a Hightouch Integration.
- [Tracking Jobs](https://docs.datafold.com/integrations/bi-data-apps/tracking-jobs.md): Track the completion and success of your data app integration syncs.
- [Integrate with Code Repositories](https://docs.datafold.com/integrations/code-repositories.md): Connect your code repositories with Datafold.
- [GitHub](https://docs.datafold.com/integrations/code-repositories/github.md): Connect Datafold to GitHub to enable automated data diffs on pull requests, CI/CD testing integration, and code-level lineage tracking.
- [GitLab](https://docs.datafold.com/integrations/code-repositories/gitlab.md)
- [Bitbucket](https://docs.datafold.com/integrations/code-repositories/bitbucket.md)
- [Azure DevOps](https://docs.datafold.com/integrations/code-repositories/azure-devops.md)
- [Deployment Options](https://docs.datafold.com/datafold-deployment/datafold-deployment-options.md): Datafold is a web-based application with multiple deployment options, including multi-tenant SaaS and dedicated cloud (either customer- or Datafold-hosted).
- [Datafold VPC Deployment on AWS](https://docs.datafold.com/datafold-deployment/dedicated-cloud/aws.md): Learn how to deploy Datafold in a Virtual Private Cloud (VPC) on AWS.
- [Datafold VPC Deployment on GCP](https://docs.datafold.com/datafold-deployment/dedicated-cloud/gcp.md): Learn how to deploy Datafold in a Virtual Private Cloud (VPC) on GCP.
- [Datafold VPC Deployment on Azure](https://docs.datafold.com/datafold-deployment/dedicated-cloud/azure.md): Learn how to deploy Datafold in a Virtual Private Cloud (VPC) on Azure.
- [Compliance & Trust Center](https://docs.datafold.com/security/compilance-trust-center.md)
- [Securing Connections](https://docs.datafold.com/security/securing-connections.md): Datafold supports multiple options to secure connections between your resources (e.g., databases and BI tools) and Datafold.
- [User Roles and Permissions](https://docs.datafold.com/security/user-roles-and-permissions.md): Datafold uses role-based access control to manage user permissions and actions.
- [Service Accounts](https://docs.datafold.com/security/service-accounts.md): Machine identities for CI, integrations, and scripts. Service accounts own their own API keys, inherit permissions from groups, and are managed independently of human users.
- [MCP Tool Permissions](https://docs.datafold.com/security/mcp-tool-permissions.md): Which permissions each MCP tool requires. Use this reference when scoping a service account's group for MCP use.
- [Single Sign-On](https://docs.datafold.com/security/single-sign-on.md): Set up Single Sign-On with one of the following options.
- [Okta (OIDC)](https://docs.datafold.com/security/single-sign-on/okta.md): Configure Okta OIDC single sign-on (SSO) for Datafold. Step-by-step setup instructions for authenticating your team with Okta.
- [Google OAuth](https://docs.datafold.com/security/single-sign-on/google-oauth.md): Configure Google OAuth single sign-on (SSO) for Datafold. Step-by-step setup instructions for authenticating your team with Google.
- [SAML](https://docs.datafold.com/security/single-sign-on/saml.md): SAML (Security Assertion Markup Language) is a protocol that enables secure user authentication by integrating Identity Providers (IdPs) with Service Providers (SPs).
- [Group provisioning](https://docs.datafold.com/security/single-sign-on/saml/group-provisioning.md): Automatically sync group membership with your SAML Identity Provider (IdP).
- [Okta](https://docs.datafold.com/security/single-sign-on/saml/examples/okta.md)
- [Microsoft Entra ID](https://docs.datafold.com/security/single-sign-on/saml/examples/microsoft-entra-id-configuration.md): Configure Microsoft Entra ID (Azure AD) as a SAML identity provider for Datafold SSO. Step-by-step setup and configuration guide.
- [Google](https://docs.datafold.com/security/single-sign-on/saml/examples/google.md)
- [Support](https://docs.datafold.com/support/support.md): Datafold offers multiple support channels to assist users with troubleshooting and inquiries.
- [FAQ](https://docs.datafold.com/support/faq-redirect.md)
- [Datafold API](https://docs.datafold.com/api-reference/datafold-api.md): Datafold REST API reference for programmatic access to data diffs, data sources, CI runs, monitors, BI integrations, and more.
- [Introduction](https://docs.datafold.com/api-reference/introduction.md): Get started with the Datafold REST API. Learn how to authenticate, obtain an API key, and make your first API call.
- [MCP Server](https://docs.datafold.com/api-reference/mcp-server-setup.md): Connect AI assistants to Datafold using the Model Context Protocol
- [List CI runs](https://docs.datafold.com/api-reference/ci/list-ci-runs.md): List all CI runs for a given CI configuration via the Datafold API.
- [Trigger a PR/MR run](https://docs.datafold.com/api-reference/ci/trigger-a-prmr-run.md): Trigger a PR/MR diff run for a CI configuration via the Datafold API.
- [Upload PR/MR changes](https://docs.datafold.com/api-reference/ci/upload-prmr-changes.md): Upload PR/MR changes for a specific pull request via the Datafold API.
- [List data sources](https://docs.datafold.com/api-reference/data-sources/list-data-sources.md): List all configured data sources in your Datafold organization via the API.
- [Create a data source](https://docs.datafold.com/api-reference/data-sources/create-a-data-source.md): Create a new data source connection via the Datafold API.
- [Get data source testing results](https://docs.datafold.com/api-reference/data-sources/get-data-source-testing-results.md): Retrieve the testing results for a data source connection via the Datafold API.
- [List data source types](https://docs.datafold.com/api-reference/data-sources/list-data-source-types.md): List all supported data source types available in the Datafold API.
- [Get a data source](https://docs.datafold.com/api-reference/data-sources/get-a-data-source.md): Retrieve details of a specific data source by ID via the Datafold API.
- [Get a data source summary](https://docs.datafold.com/api-reference/data-sources/get-a-data-source-summary.md): Get a summary of a specific data source by ID via the Datafold API.
- [Test a data source connection](https://docs.datafold.com/api-reference/data-sources/test-a-data-source-connection.md): Test the connection of a specific data source via the Datafold API.
- [List data diffs](https://docs.datafold.com/api-reference/data-diffs/list-data-diffs.md): List all data diffs in your Datafold organization via the API.
- [Create a data diff](https://docs.datafold.com/api-reference/data-diffs/create-a-data-diff.md): Create a new data diff to compare datasets via the Datafold API.
- [Get a data diff](https://docs.datafold.com/api-reference/data-diffs/get-a-data-diff.md): Retrieve details of a specific data diff by ID via the Datafold API.
- [Update a data diff](https://docs.datafold.com/api-reference/data-diffs/update-a-data-diff.md): Update the configuration of an existing data diff via the Datafold API.
- [Get a data diff summary](https://docs.datafold.com/api-reference/data-diffs/get-a-data-diff-summary.md): Get the summary results of a specific data diff via the Datafold API.
- [List all integrations](https://docs.datafold.com/api-reference/bi/list-all-integrations.md): List all BI integrations configured in your Datafold organization via the API.
- [Create a DBT BI integration](https://docs.datafold.com/api-reference/bi/create-a-dbt-bi-integration.md): Create a dbt BI integration for lineage tracking via the Datafold API.
- [Update a DBT BI integration](https://docs.datafold.com/api-reference/bi/update-a-dbt-bi-integration.md): Update an existing dbt BI integration via the Datafold API.
- [Create a Hightouch integration](https://docs.datafold.com/api-reference/bi/create-a-hightouch-integration.md): Create a Hightouch integration for lineage tracking via the Datafold API.
- [Update a Hightouch integration](https://docs.datafold.com/api-reference/bi/update-a-hightouch-integration.md): Update an existing Hightouch integration via the Datafold API.
- [Create a Looker integration](https://docs.datafold.com/api-reference/bi/create-a-looker-integration.md): Create a Looker BI integration for lineage tracking via the Datafold API.
- [Update a Looker integration](https://docs.datafold.com/api-reference/bi/update-a-looker-integration.md): Update an existing Looker BI integration via the Datafold API.
- [Create a Mode Analytics integration](https://docs.datafold.com/api-reference/bi/create-a-mode-analytics-integration.md): Create a Mode Analytics BI integration for lineage tracking via the Datafold API.
- [Update a Mode Analytics integration](https://docs.datafold.com/api-reference/bi/update-a-mode-analytics-integration.md): Update an existing Mode Analytics BI integration via the Datafold API.
- [Create a Tableau integration](https://docs.datafold.com/api-reference/bi/create-a-tableau-integration.md): Create a Tableau BI integration for lineage tracking via the Datafold API.
- [Update a Tableau integration](https://docs.datafold.com/api-reference/bi/update-a-tableau-integration.md): Update an existing Tableau BI integration via the Datafold API.
- [Get an integration](https://docs.datafold.com/api-reference/bi/get-an-integration.md): Retrieve details of a specific BI integration by ID via the Datafold API.
- [Remove an integration](https://docs.datafold.com/api-reference/bi/remove-an-integration.md): Remove a BI integration by ID via the Datafold API.
- [Sync a BI integration](https://docs.datafold.com/api-reference/bi/sync-a-bi-integration.md): Trigger a sync for a specific BI integration via the Datafold API.
- [Datafold SDK](https://docs.datafold.com/api-reference/datafold-sdk.md): Use the Datafold SDK for programmatic access to data diffs, CI artifact uploads, and integration with your data pipelines.
- [Get Audit Logs](https://docs.datafold.com/api-reference/audit-logs/get-audit-logs.md): Retrieve audit logs for your Datafold organization via the API.
- [List CI runs](https://docs.datafold.com/api-reference/ci/list-ci-runs.md): List all CI runs for a given CI configuration via the Datafold API.
- [Trigger a PR/MR run](https://docs.datafold.com/api-reference/ci/trigger-a-prmr-run.md): Trigger a PR/MR diff run for a CI configuration via the Datafold API.
- [Upload PR/MR changes](https://docs.datafold.com/api-reference/ci/upload-prmr-changes.md): Upload PR/MR changes for a specific pull request via the Datafold API.
- [List data sources](https://docs.datafold.com/api-reference/data-sources/list-data-sources.md): List all configured data sources in your Datafold organization via the API.
- [Create a data source](https://docs.datafold.com/api-reference/data-sources/create-a-data-source.md): Create a new data source connection via the Datafold API.
- [Get data source testing results](https://docs.datafold.com/api-reference/data-sources/get-data-source-testing-results.md): Retrieve the testing results for a data source connection via the Datafold API.
- [List data source types](https://docs.datafold.com/api-reference/data-sources/list-data-source-types.md): List all supported data source types available in the Datafold API.
- [Get a data source](https://docs.datafold.com/api-reference/data-sources/get-a-data-source.md): Retrieve details of a specific data source by ID via the Datafold API.
- [Execute a SQL query against a data source](https://docs.datafold.com/api-reference/data-sources/execute-a-sql-query-against-a-data-source.md): Executes a SQL query against the specified data source and returns the results.
- [Get a data source summary](https://docs.datafold.com/api-reference/data-sources/get-a-data-source-summary.md): Get a summary of a specific data source by ID via the Datafold API.
- [Test a data source connection](https://docs.datafold.com/api-reference/data-sources/test-a-data-source-connection.md): Test the connection of a specific data source via the Datafold API.
- [List data diffs](https://docs.datafold.com/api-reference/data-diffs/list-data-diffs.md): List all data diffs in your Datafold organization via the API.
- [Create a data diff](https://docs.datafold.com/api-reference/data-diffs/create-a-data-diff.md): Create a new data diff to compare datasets via the Datafold API.
- [Get a data diff](https://docs.datafold.com/api-reference/data-diffs/get-a-data-diff.md): Retrieve details of a specific data diff by ID via the Datafold API.
- [Update a data diff](https://docs.datafold.com/api-reference/data-diffs/update-a-data-diff.md): Update the configuration of an existing data diff via the Datafold API.
- [Cancel a running data diff](https://docs.datafold.com/api-reference/data-diffs/cancel-a-running-data-diff.md): Cancels a data diff that is currently queued or running.
- [Get a human-readable summary of a DataDiff comparison](https://docs.datafold.com/api-reference/data-diffs/get-a-human-readable-summary-of-a-datadiff-comparison.md): Retrieves a comprehensive, human-readable summary of a completed data diff.
- [Get a data diff summary](https://docs.datafold.com/api-reference/data-diffs/get-a-data-diff-summary.md): Get the summary results of a specific data diff via the Datafold API.
- [Get column downstreams](https://docs.datafold.com/api-reference/explore/get-column-downstreams.md): Retrieve a list of columns or tables which depend on the given column.
- [Get column upstreams](https://docs.datafold.com/api-reference/explore/get-column-upstreams.md): Retrieve a list of columns or tables which the given column depends on.
- [Get table downstreams](https://docs.datafold.com/api-reference/explore/get-table-downstreams.md): Retrieve a list of tables which depend on the given table.
- [Get table upstreams](https://docs.datafold.com/api-reference/explore/get-table-upstreams.md): Retrieve a list of tables which the given table depends on.
- [List all integrations](https://docs.datafold.com/api-reference/bi/list-all-integrations.md): List all BI integrations configured in your Datafold organization via the API.
- [Create a DBT BI integration](https://docs.datafold.com/api-reference/bi/create-a-dbt-bi-integration.md): Create a dbt BI integration for lineage tracking via the Datafold API.
- [Update a DBT BI integration](https://docs.datafold.com/api-reference/bi/update-a-dbt-bi-integration.md): Update an existing dbt BI integration via the Datafold API.
- [Create a Hightouch integration](https://docs.datafold.com/api-reference/bi/create-a-hightouch-integration.md): Create a Hightouch integration for lineage tracking via the Datafold API.
- [Update a Hightouch integration](https://docs.datafold.com/api-reference/bi/update-a-hightouch-integration.md): Update an existing Hightouch integration via the Datafold API.
- [Create a Looker integration](https://docs.datafold.com/api-reference/bi/create-a-looker-integration.md): Create a Looker BI integration for lineage tracking via the Datafold API.
- [Update a Looker integration](https://docs.datafold.com/api-reference/bi/update-a-looker-integration.md): Update an existing Looker BI integration via the Datafold API.
- [Create a Mode Analytics integration](https://docs.datafold.com/api-reference/bi/create-a-mode-analytics-integration.md): Create a Mode Analytics BI integration for lineage tracking via the Datafold API.
- [Update a Mode Analytics integration](https://docs.datafold.com/api-reference/bi/update-a-mode-analytics-integration.md): Update an existing Mode Analytics BI integration via the Datafold API.
- [Create a Power BI integration](https://docs.datafold.com/api-reference/bi/create-a-power-bi-integration.md)
- [Update a Power BI integration](https://docs.datafold.com/api-reference/bi/update-a-power-bi-integration.md): Updates the integration configuration. Returns the integration with changed fields.
- [Create a Tableau integration](https://docs.datafold.com/api-reference/bi/create-a-tableau-integration.md): Create a Tableau BI integration for lineage tracking via the Datafold API.
- [Update a Tableau integration](https://docs.datafold.com/api-reference/bi/update-a-tableau-integration.md): Update an existing Tableau BI integration via the Datafold API.
- [Get an integration](https://docs.datafold.com/api-reference/bi/get-an-integration.md): Retrieve details of a specific BI integration by ID via the Datafold API.
- [Remove an integration](https://docs.datafold.com/api-reference/bi/remove-an-integration.md): Remove a BI integration by ID via the Datafold API.
- [Sync a BI integration](https://docs.datafold.com/api-reference/bi/sync-a-bi-integration.md): Trigger a sync for a specific BI integration via the Datafold API.
- [List Monitors](https://docs.datafold.com/api-reference/monitors/list-monitors.md)
- [Create a Data Diff Monitor](https://docs.datafold.com/api-reference/monitors/create-a-data-diff-monitor.md)
- [Create a Metric Monitor](https://docs.datafold.com/api-reference/monitors/create-a-metric-monitor.md)
- [Create a Schema Change Monitor](https://docs.datafold.com/api-reference/monitors/create-a-schema-change-monitor.md)
- [Create a Data Test Monitor](https://docs.datafold.com/api-reference/monitors/create-a-data-test-monitor.md)
- [Get Monitor](https://docs.datafold.com/api-reference/monitors/get-monitor.md)
- [Delete a Monitor](https://docs.datafold.com/api-reference/monitors/delete-a-monitor.md)
- [Trigger a run](https://docs.datafold.com/api-reference/monitors/trigger-a-run.md)
- [List Monitor Runs](https://docs.datafold.com/api-reference/monitors/list-monitor-runs.md)
- [Get Monitor Run](https://docs.datafold.com/api-reference/monitors/get-monitor-run.md)
- [Toggle a Monitor](https://docs.datafold.com/api-reference/monitors/toggle-a-monitor.md)
- [Update a Monitor](https://docs.datafold.com/api-reference/monitors/update-a-monitor.md)
- [Overview](https://docs.datafold.com/faq/overview.md): Get answers to the most common questions regarding our product.
- [Data Diffing](https://docs.datafold.com/faq/data-diffing.md): Frequently asked questions about Datafold's data diffing capabilities, including supported databases, data types, performance, and use cases.
- [CI/CD Testing](https://docs.datafold.com/faq/ci-cd-testing.md): Frequently asked questions about Datafold's CI/CD testing integration, including staging environments, diff performance, and automated data quality checks.
- [Data Reconciliation](https://docs.datafold.com/faq/data-reconciliation.md): Frequently asked questions about cross-database data reconciliation with Datafold, including how diffing works, scaling, and handling schema differences.
- [Data Monitoring and Observability](https://docs.datafold.com/faq/data-monitoring-observability.md): Frequently asked questions about Datafold's data monitoring and observability capabilities, including how it compares to other data observability tools.
- [Integrating Datafold with dbt](https://docs.datafold.com/faq/datafold-with-dbt.md): Frequently asked questions about using Datafold with dbt, including CI/CD setup for dbt Core and dbt Cloud, data diff performance, and testing workflows.
- [Data Storage and Security](https://docs.datafold.com/faq/data-storage-and-security.md)
- [Performance and Scalability](https://docs.datafold.com/faq/performance-and-scalability.md)
- [Resource Management](https://docs.datafold.com/faq/resource-management.md): Frequently asked questions about Datafold's resource consumption, data warehouse cost impact, and performance optimization.

## OpenAPI Specs

- [openapi-public](/openapi-public.json)

## Optional

- [About Datafold](https://www.datafold.com/)
- [Blog](https://www.datafold.com/blog?)


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